Prevention

Automated Rigo Classification: An Innovative Artificial Intelligence System.

Although there is variation in clinicians' application of the Rigo classification system (RCS) to adolescent idiopathic scoliosis, no artificial intelligence (AI) models have been developed to standardize the RCS specifically. This study aimed to develop an AI model that applies the RCS to X-rays, and compare its parameter measurements, processing time, and classification accuracy to human observe...

Toward Precision Cardiac Rehabilitation: Current Limitations and Future Opportunities of Omics and Artificial Intelligence.

Cardiovascular disease involves complex molecular, cellular, and physiological derangements that present challenges for traditional diagnostic and therapeutic approaches. Precision medicine is an evolving field that seeks to tailor interventions according to an individual's genetic, molecular, and physiological characteristics. By leveraging advanced omics approaches, including genomics, proteomic...

Artificial intelligence in pathology: a framework for preserving brain capital in the diagnostic apex.

AIM: To present a five-criterion calibration framework for evaluating artificial intelligence (AI) tools in pathology centered on preserving "brain ca...

Physical therapy using digital therapeutics in infants with congenital muscular torticollis: a pilot study.

Congenital muscular torticollis (CMT) is a common musculoskeletal problem associated with unilateral sternocleidomastoid muscle stiffness. We evaluate...

Predicting major adverse cardiovascular and cerebrovascular events in chronic heart failure: a machine learning study.

BACKGROUND: Heart failure (HF) is a clinical syndrome characterized by impaired cardiac diastolic and systolic function due to structural or functiona...

Comparison of ChatGPT and dietitians in formulating diet plans and recommendations for patients with cardiometabolic diseases.

BACKGROUND: Artificial Intelligence (AI) is transforming personalized medicine, yet its efficacy constitutes a dynamic factor in the field of health a...

AI-Powered Resting 12-Lead Electrocardiogram Algorithm for Predicting Low Peak Oxygen Consumption: Development and Validation Study.

BACKGROUND: Low peak oxygen consumption (V̇O2) is associated with higher cardiovascular and all-cause mortality, while improvements in peak V̇O2 reduc...

Development and prospective evaluation of a real-time deep learning model for inpatient hypoglycemia prediction.

Inpatient hypoglycemia is associated with increased morbidity, mortality, length of stay, and healthcare costs, yet current management remains reactiv...

Predicting poor health-related quality of life among Chinese adolescents using explainable machine learning: the role of school adjustment, family context, and lifestyle factors.

BACKGROUND: Adolescents' health-related quality of life (HRQoL) is influenced by multiple domains, including school, family, and individual lifestyle....

Combinations of single gene predictors with AI-driven polygenic precision therapies in cardiovascular diseases.

Pharmacogenomics (PGx) is transforming how we treat cardiovascular disease (CVD) by enabling us to select and dose drugs based on our genetic profiles...

A multimodal approach to equine thoracolumbar myofascial pain: integrating clinical examination, AI-based gait analysis, and the ridden horse pain ethogram.

BACKGROUND: Myofascial pain syndrome (MPS) is considered highly prevalent in horses, yet it is frequently underdiagnosed due to limited understanding ...

Reconfiguring biofortification strategies to transform food systems and address micronutrient deficiency of the 21st century.

Despite achieving substantial progress in caloric food security, micronutrient deficiencies remain a major global health challenge, highlighting a per...

A round-robin exercise for the precise prediction of aqueous solubility of organic chemicals using chemometric, machine learning, and stacking ensemble of deep learning models.

Aqueous solubility is an important property for assessing the druggability and ecotoxicological effects of molecules. Successful drug candidates shoul...

Revisiting satisfaction with life: A hybrid study based on linear models and machine learning.

PURPOSE: Based on the Health Action Process Approach (HAPA) theory, this study examines how Health Literacy is associated with Satisfaction with Life ...

A quarter-century of progress: innovations in lipid medicine that transformed cardiovascular prevention.

This TimeCapsule reviews the major transformations in lipid metabolism and cardiovascular disease prevention during the first quarter of the 21st cent...

Artificial intelligence as a clinical tool builder: Development and early implementation of an artificial intelligence-assisted hand therapy exercise application.

Physical activity level and its determinants in patients with cancer: a secondary analysis using a decision-tree approach.

PURPOSE: Low physical activity is associated with poorer outcomes in patients with cancer. Understanding the determinants of physical activity is esse...

Smartwatch-derived exercise metrics as predictors of early hypertension: a prospective observational study.

BACKGROUND: Early identification of individuals at risk for hypertension is essential for effective cardiovascular disease. Physiological and activity...

Can AI chatbots effectively respond inquiries for patients with Pulmonary Arterial Hypertension about exercise and physical activity: A comparative study of three chatbots.

OBJECTIVE: The utilization of artificial intelligence-based chatbots in the healthcare field is increasingly prevalent. Nonetheless, the quality of re...

A Flexible Wireless Passive Platform for Decoupled Electrolyte and Temperature Sensing Toward Heat‑Stress Assessment.

Strenuous exercise and heat exposure can significantly elevate core body temperature and induce profuse sweating, leading to dehydration, electrolyte ...